Biodiversity and Conservation Volume 9 Number 2, February 2017 ISSN 2141-243X

International Journal of Biodiversity and Conservation Volume 9 Number 2, February 2017 ISSN 2141-243X

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Yusuf Garba Bayero University, Kano P.M.B 3011 Kano - Nigeria Department of Animal Science, Faculty of Agriculture, Bayero University, Kano

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Table of Contents: Volume 9 Number 2 February, 2017

ARTICLES

Diversity of ectomycorrhizal fungal fruit bodies in Comoé National Park, a Biosphere Reserve and World Heritage in Côte d’Ivoire (West Africa) 27 Linda Patricia Louyounan Vanié-Léabo, Nourou Soulemane Yorou, N´Golo Abdoulaye Koné, François N’Guessan Kouamé, André De Kesel and Daouda Koné

The attitudes and practices of local people towards wildlife in Chebera Churchura national park, Ethiopia 45 Aberham Megaze, Mundanthra Balakrishnan and Gurja Belay

Vol. 9(2), pp. 27-44, February 2017 DOI: 10.5897/IJBC2016.0999 Article Number: B31F0A662715 International Journal of Biodiversity ISSN 2141-243X Copyright © 2017 and Conservation Author(s) retain the copyright of this article http://www.academicjournals.org/IJBC

Full Length Research Paper

Diversity of ectomycorrhizal fungal fruit bodies in Comoé National Park, a Biosphere Reserve and World Heritage in Côte d’Ivoire (West Africa)

Linda Patricia Louyounan Vanié-Léabo1,2*, Nourou Soulemane Yorou3, N´Golo Abdoulaye Koné4, François N’Guessan Kouamé1,5, André De Kesel6 and Daouda Koné1,2

1WASCAL Graduate Study Program (GSP) Climate Change and Biodiversity, University Félix Houphouët-Boigny, B.P. 582 Abidjan 22, Côte d‟Ivoire. 2Laboratoire de Physiologie Végétale, U.F.R. Biosciences, Université Félix Houphouët-Boigny, Côte d‟Ivoire. 3Faculty of Agronomy, University of Parakou, BP 123 Parakou, Bénin. 4 Station de Recherche en Ecologie du Parc National de la Comoé, U.F.R. des Sciences de la Nature, Université Nangui Abrogoua, 28 BP 847 Abidjan 28, Côte d‟Ivoire. 5Laboratoire de Botanique, U.F.R. Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte 6Botanic Garden Meise, Nieuwelaan 38, B-1860 Meise, Belgium.

Received 1 June, 2016; Accepted 21 December, 2016

The key role of ectomycorrhizal (EcM) fungi in ecosystems functioning has been demonstrated worldwide. However, their diversity, spatial distribution, fruiting phenology and production as influenced by climatic parameters variability remain poorly understood in tropical African forests. Weekly surveys were conducted from April to early October 2014 at the Comoé National Park (CNP), Côte d’Ivoire (West Africa) in 09 permanent plots established in Isoberlinia doka (IW), Uapaca togoensis (UW) and Mixed (MW) woodlands. Non metric multidimensional scaling (NMDS) of EcM fungi abundance was run to assess the influence of environment tal parameters on fungi distribution using the package VEGAN. Hierarchical clustering based on dissimilarity and indicator species analysis were run to characterize fungi communities. Analyses were computed with the statistical program R. A total of 123 EcM fungi species belonging to 23 genera and 09 families were collected at CNP. Simpson diversity (1- D) and evenness were 0.97 and 0.54, 0.97 and 0.61, 0.96 and 0.52 for IW, MW and UW respectively. Yet, weekly-based species accumulation curves did not reach an asymptote. Stem density of U. togoensis Pax (UTDen) and I. doka Craib & Stapf were the most important tree parameters influencing EcM fungi distribution (respectively r2 = 0.92 / p-value = 0.002 and r2 = 0.83 / p-value = 0.018). Two sites groups were distinguished and four indicators species were identified.

Key words: EcM fungi, fruit bodies, diversity, indicator species.

INTRODUCTION

Productivity, diversity and composition of plant directly inﬂuenced by belowground micro-organisms from communities have been demonstrated indirectly and which plant symbionts play a key role (Van Der Heijden 28 Int. J. Biodivers. Conserv.

et al., 2008; Van Der Heijden and Horton, 2009). is actually difficult to predict the exact response of plant Globally, over 90% of terrestrial plants depend upon an diversity to climate change as many investigations are ecological relationship with soil fungi for their growth and still needed to understand the resilience, adaptation regeneration (Smith and Read, 2008; Singh et al., 2011; and/or migration following fluctuation of climatic Dickie et al., 2014). This relationship termed mycorrhiza parameters. is the most prevalent symbiosis on Earth, including As both partners are living more or less obligatory and cultivated plants, herbaceous species and forest trees. intimately, any possible change that affect host plants is Generally, autotrophic plants provide carbohydrates to also expected to influence the symbiotic fungi. In their fungi partners, which in turn improve host temperate and boreal zone, rainfall and moisture performance by enhancing mineral nutrient uptake from availability have been demonstrated as critical to EcM soil, especially nitrogen (N) and phosphorus (P). fruiting and natural production (O'Dell et al., 2000; Gange Symbiotic fungi enhance plant tolerance to environmental et al., 2007; Kauserud et al., 2010). Furthermore, long stress caused by low soil water potential, toxic heavy term observations of fungal phenology in temperate metals, salinity, herbivores and root pathogens (Smith forests reveal that fruit bodies production and temporal and Read, 2008; Singh et al., 2011; Dickie et al., 2014). changes are strongly influenced by either increasing Among mycorrhizas types, ectomycorrhiza (EcM) is the temperature (Kauserud et al., 2008; Kauserud et al., most advanced one (Moore et al., 2011) involving mostly 2010) and/or rainfalls (Krebs et al., 2008). Due to their higher plants and fungi (Piepenbring, 2015). Thus, EcM vital role in forest ecosystems and the sensitivity of their fungi have an important position in the plant-soil interface respiration to high temperature and strong seasonality (Ceulemans et al., 1999) worldwide, playing a key role in (Vargas et al., 2010; Bahram et al., 2012), EcM fungi the growth and regeneration of forest trees, and in represent best candidates to investigate for a better ecosystems functioning. understanding of ecosystems response to global warming However, the global biodiversity is under decline since and especially in carbon sequestration capability (Simard the 19th century due to serious climate, environmental and Austin, 2010; Orwin et al., 2011; Büntgen et al., and ecological changes through human activities around 2012; Büntgen et al., 2013; Boddy et al., 2014). the globe. The global climate system is actually modified Unfortunately, the response of EcM communities to by increased greenhouse gases (GHG) in the global warming and environmental changes is scarcely atmosphere subsequently to unrestrained deforestation, addressed in tropical zones and especially in tropical. In fossil fuel combustion and other anthropogenic activities Sudanian woodlands of Africa, a strong variability has (WMO, 2007). Few key parameters of global change are been noticed regarding species richness and community among other trend towards warming (increasing structure throughout the fruiting season (Yorou et al., temperature), increase of atmospheric CO2 and 2001). Nevertheless, the authors failed to link species disturbance in the distribution, seasonality and amount of composition, community structure and productivity rainfalls. It is predicted that Earth surface temperature will patterns of EcM with either the local temperature or soil increase from 0.3°C to 1.7°C under scenario RCP2.6 by humidity. To our knowledge, that study is the only one in the end of the 21st century (2081–2100) whilst the tropical Africa addressing the impact of climate atmospheric carbon level is continuously increasing parameters on wild EcM fungi phenology and (IPCC, 2014). Though the impact of global change on productions. Now, knowing temporal change in the ecosystems is not yet adequately addressed, it is phenology and production distribution, and their expected that many changes in global biodiversity and determinants is essential in the valorisation of natural ecosystem functions will occur. High temperature is productions of wild edible EcM fungi that amounts to expected to alter tree phenology, plant growth and thousand tons annually and involves many rural women distribution toward migration and adaptation ecozones (Yorou et al., 2001, 2014; Boa, 2004). However, a (Montoya and Raffaelli, 2010) but also to increase the prerequisite to climate impact assessment is the analysis length of the growing season (Walther et al., 2002; Morin of EcM fungi diversity and the evaluation of possible et al., 2007), and the aboveground growth and other natural underlying mechanisms of richness pattern reproductive effort of plants (Hollister et al., 2005). At the (Tedersoo and Nara, 2010). It has been demonstrated other side, elevated atmospheric CO2 and nitrogen will that the impacts of atmospheric carbon dioxide likely increase the rate of net photosynthesis by 40 to enrichment is more clear on fruit bodies than on below- 80% (Körner et al., 2005), the allocation of carbon to the ground tips (Andrew and Lilleskov, 2009; Pickles et al., plant roots (Janssens et al., 2005) and the production of 2012). Therefore, this study aims to (1) assess the leaves, wood and coarse roots (Hyvönen et al., 2007). It diversity (species richness and community structure) of

*Corresponding author. E-mail: [email protected]

Author(s) agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Vanié Léabo et al. 29

EcM fungi species through fruit bodies diversity and (2) EcM fungal fruit bodies collect and handling assess the spatial variability of the community composition following habitat characteristics (plant and EcM fungal fruit bodies (EFFB) were collected in each plot following parallel bands of 2 m large. To avoid missing short living species, soil parameters) at local scale. We hypothesised that (1) each plot was visited once a week from April to early October 2014 African protected areas harbour a great diversity of EcM as implemented by Yorou et al. (2001). We recorded the nearest fungi with many species likely new to sciences, and (2) EcM partner trees to each sampled fruit body and geographic host plants and soil structural parameters drive the coordinates using GPS Garmin GPSMAP® 62stc (Garmin communities of EcM fungi. International Inc., Olathe, KS, USA). To facilitate future comparison and morphological identification of species, technical photographs of most representative fruit bodies per species (at different development stage, when applicable) were taken on field and at the MATERIALS AND METHODS base camp using a Canon EOS 1000D digital cameras. Fresh macroscopic features were then recorded from specimens, using Study site standardized descriptions sheets (size, shape; colour and any change with time; presence/absence of ephemeral structures; type The Comoé National Park (CNP) is located in the North-East of of hymenophore, its colour and organization; etc.) developed for Côte d‟Ivoire (8°32' - 9°32'N, 3°01' - 4°24'W) between the towns of tropical African fungi (De Kesel et al., 2002; Eyi Ndong et al., 2011). Bouna and Dabakala, and south of the border with Burkina Faso. Afterwards, Fruit bodies per collection were counted, weighted, The CNP covers about 11 500 km² (Hennenberg, 2004) and is labelled and representative specimens were dried at 40˚C for 24 h. presently one of the largest national park in West Africa (Poilecot et Labelled collections were conserved with basic ecological data al., 1991). Initially erected as a game park since 1926 („Refuge (habitat type, substrate, putative nearest partner tree, exposition to Nord de la Côte d‟Ivoire‟) and then established as national park in sun, etc.) as herbarium materiel at the WASCAL GSP Climate 1968, Comoé was approved in 1983 and declared as Biosphere Change and Biodiversity, University Felix Houphouet-Boigny (Côte Reserve and World Nature Heritage by the UNESCO (Hennenberg, d‟Ivoire). 2004). The identification of collected fungal species was performed The park is located on the large granite stand of West Africa and based on morphological features at Botanic Garden of Munich in is characterized by a smooth and level relief. Soils are Germany and Botanic Garden Meise in Belgium by experts (De impoverished sandy to loamy ferralsols above Precambrian granites Kesel and Yorou, personal communications). Appropriate keys and with small areas of lateritic crusts or banks outcrop at some places numerous illustrated monographs on fungi of Central and Western (Hennenberg et al., 2005). The climate is a Guineo- Africa (series of “Flore Iconographique des Champignons du Congolian/Sudanian transitional type, a sub-humid tropical climate Congo” and “Flore illustrée des Champignons d‟Afrique Centrale”) (Chidumayo et al., 2010) with mean annual rainfall of 1 011 mm were used. These series include monographs on Amanita spp. falling mainly between March and October. The mean annual (Beeli, 1935), Boletineae and Cantharellus spp. (Heinemann, 1954, temperature is 26.5 to 27°C (Koulibaly, 2008). CNP vegetation is 1959, 1966), Scleroderma spp.(Dissing and Lange, 1963) and transitional ranging from forests to savannas including riparian Russula spp. (Buyck, 1993, 1994, 1997) and Lactarius spp. (Heim, grasslands (Poilecot et al., 1991; Hennenberg et al., 2005). 1955). An additional monograph on Lactarius spp. (Verbeken and Walleyn, 2010) was also used. Species names and nomenclatural aspects were checked in index fungorium Selection of habitat types and establishment of permanent (http://www.indexfungorum.org/Names/Names.asp). Moreover, plots molecular-based identification of representative specimens per species was performed (Gardes and Bruns, 1993; Maba et al., One-week exploratory survey was undertaken within the accessible 2013) at both abovementioned research institutes. Results of parts of the park in November 2013 to identify appropriate study molecular analysis along with metabarcoding analyses of sites. Based on available vegetation maps (Poilecot et al., 1991; composite soil samples (for belowground fungi diversity Lauginie, 2007), three habitat types were selected with regard to; assessment) will be presented in a manuscript in preparation. (1) The presence and abundance of known EcM partners trees, members of Caesalpiniaceae and Phyllantaceae (to ensure collection of symbiotic fungi and assess partners influence on Habitat types characterisation fungal species distribution) and (2) the distance to the Ecological Research Station of Comoé, our base camp (for rapid handling of Biotic and abiotic variables were collected to assess their possible fragile specimens during hot and wet season). influence on EFFB occurrence and spatial distribution. The different habitat types were at least 300 m away from one First, systematic inventory of plant species and total canopy another and included: cover estimation within plots were performed in April 2014 according to the phytosociological method (Braun-Blanquet, 1932). Habitat type 1: Isoberlinia doka Craib & Stapf Woodland (IW); Primary identification of plants specimens were done with field Habitat type 2: Mixed Woodland (MW); guide (Arbonnier, 2004) and completed with collected herbarium Habitat type 3: Uapaca togoensis Pax Woodland (UW). materials by experts from the Laboratoire de Botanique of the University Felix Houphouet-Boigny in Abidjan, Côte d‟Ivoire. In each selected habitat type, three permanent plots of 30 m × 30 m However, for statistical analyses, only woody species with diameter each have been established by mean of a hectometer, making a at breast height (dbh) equal or above (≥) 10 cm were considered. total of nine plots (Figure 1). They have been labelled FiPi with Fi Therefore, in addition to plant species richness, structural representing the habitat type and Pi the plot. All nine (09) plots parameters (number of stems and dbh per species and per plot) have been geo-referenced by recording the coordinates of each were recorded. corner with a GPS Garmin GPSMAP® 62stc (Garmin International Second, soil cores were collected with a 10 cm × 10 cm - 10 cm Inc., Olathe, KS, USA). Plots within a habitat type were spaced at depth auger at each corner and the center of each plot at mid-rainy least by 10 m one another, according to tree partners‟ presence season (late July). All five cores were mixed to make a composite and density (Table 1). soil which was air-dried and passed through a 2-mm sieve. Three 30 Int. J. Biodivers. Conserv.

Figure 1. Location of Comoé National Park (north east of Côte d‟Ivoire) and established permanent plots within it (south west of the reserve).

composite soils were thus made per habitat and 200 g per Physical parameters referred to soil texture: Clay, fine and 2. Determination of extractable cations‟ content was sample were used to assess soil granulometry, pH and coarse Silt, fine and coarse Sand. They were determined achieved according to standard NFX 31-130 (AFNOR, minerals contents. Chemical parameters assessed were as follows: 1999). pH (H2O), Carbon (C), Nitrogen (N), soil organic carbon 3. Determination of organic and total carbon: The total (SOC), ratio C/N, Total Phosphorus (TotalP), Available 1. pH (H2O) measurement was performed with a soil carbon content in soil is determined after dry combustion. Phosphorus (AvailP), Calcium (Ca) and Potassium (K). solution at a ratio 2/5 (Duchaufour and Blum, 1997). The soil‟s organic carbon content is calculated Vanié Léabo et al. 31

Table 1. Positions of permanent plots within habitat types in Comoé National Park (CNP), Cote d‟Ivoire

Habitat type Isoberlinia Woodland Mixed Woodland Uapaca Woodland Plot F1P1 F1P2 F1P3 F2P1 F2P2 F2P3 F3P1 F3P2 F3P3 Latitude (dd) 8.76264 8.762447 8.762408 8.767876 8.7676 8.768387 8.769594 8.770105 8.7703 Longitude (dd) -3.7667 -3.76719 -3.76754 -3.76588 -3.766 -3.76581 -3.76668 -3.76665 -3.767 Altitude (m) 235.13 233.17 232.64 230.40 230.79 248.19 216.23 213.81 213.62

dd: decimal degrees; m: meters

according to the method NF ISO 10694 (AFNOR, 1995). of study sites. 4. Particle size determination by sedimentation - the pipette method following the standard method NF X 31-107 (AFNOR, 2003). Habitat characterisation

Data analysis Floristic richness and dendometric parameters assessment: Number of stems and dbh per species underwent basic statistical EcM fungal fruiting bodies diversity assessment analyses as follows:

Basic estimators and indices were calculated to assess the diversity 1. Plant species density (Di), the number of stems per species per of fungi species as reflected by EFFB at plot and habitat type level. plot surface in square meters (m2), converted later in hectares (ha); They included also similarity between plots and habitat types as 2. Individual stem basal area (BAi). ⁄ , well as the number of shared species to compare communities. 2 where tree dbh in cm and BAi in m . This formula is simplified as: ;

3. Species basal area (BA ) that equals to the sum of all BA of Observed species richness and diversity assessment sp i stems of the same plant species within a plot, converted later in

hectares (ha); Presence/absence data of EFFB was used to determine (1) the 4. Total basal area (TBA), summing up the all calculated BA within observed species richness (SR: number of species) and sp a plot; composition (SC: list of species) per habitat type; (2) the total ⁄ observed species richness and composition as cumulative data of 5. Species relative dominance (SRD): ( ) . all habitat types. Thereby, the frequency of occurrence (percentage of total weeks during which a species was recruited) of fungal species was used to highlight the contribution of each species in Soil chemical and physical analysis the community (Horton and Bruns, 2001). The relative frequency of each species was calculated as the percentage of total frequency. Soil parameters evaluation was performed according to standard Assessment of fungi diversity and evenness of frequency of method as follows: species within habitat types was achieved respectively by 1. Determination of pH (H20) and content of extractable cations computing Simpson's Index of Diversity (1 – D) and Simpson‟ 2+ + + Evenness with the program Ecological Methodology (Krebs and (Ca , K , NH4 ) was performed by reading directly the digital Kenney, 2002). Simpson's Index of Diversity (1 – D) refers to the display of the pHmeter or spectrophotometer; probability that two individuals randomly selected from a sample will 2. Determination of organic and total carbon: belong to different species. Its value ranges between 0 and 1, . with M.org = organic matter (mg / kg); C.org = organic greater value corresponding to high diversity). carbon (mg/kg) 3. Particle size determination by sedimentation using the pipette method. Content of different fractions was determined as follows: Sampling representativeness: Species accumulation curves and similarity assessment 1

Sample-based species accumulation curves were constructed in 2 EstimateS ver. 9.1.0 (Colwell, 2013) using presence/absence 3 (incidence) data. The sample order was randomized 500 times without replacement for the statistical representation of the EcM 4 fungi community. In this study, “sample” referred to frequency of survey, a week-interval, against which Observed and Estimated 5 Chao 2 species accumulation curves were plotted. The similarity of our sampling to the fungi community was ⁄ 6 estimated by measuring the autosimilarity (Cao et al., 2002) between plots of each habitat type. This was calculated as mean 7 Jaccard coefficient computed with EstimateS ver. 9.1.0 software. Autosimilarity index varies from 0 (no species common to plots) to 1 With C = clay; PC+St = T are weight + clay + silt; St = silt; P1 = (same species composition in plots). Constructed week-based weight of empty tare (capsule); FSt = fine silt;P2 = Weight of empty species accumulation curves, Simpson's Index of Diversity (1 – D) tare + white; TSd = total sand; ; CSd = coarse and Simpson's evenness along with autosimilarity index served to sand; ⁄ FSd = fine sand; V = volume of the pipette; CSt assess the sampling representativeness of fungal communities = coarse silt; Pe = aliquot intake; Tt = cap weight + the total sand; 32 Int. J. Biodivers. Conserv.

Table 2. Richness of EcM fungi within selected habitat types

Fungi parameters Isoberlinia Woodland (IW) Mixed Woodland (MW) Uapaca Woodland (UW) Total Numbers of fruit bodies 1565 513 736 2814 Numbers of species 75 65 56 123 Numbers of genus 21 15 16 23 Numbers of family 9 6 6 9

Fh = humidity factor; Tc = cap weight + coarse sand; Pc = cap probability of finding the species in sites belonging to the site group” weight + clay; Tf = cap weight + fine sand. according to Dufrêne and Legendre (1997) and De Cáceres and The texture of each soil was determined using TRIANGLE, A Legendre (2009). Final, ecological distance between generated site Program For Soil Textural Classification (Gerakis and Baer, 1999). groups was calculated by Jaccard index using the R package Fossil That texture determination followed percentage of particles within (Vavrek, 2011). studied soils.

RESULTS Gradients effectiveness EcM fungi diversity Analysis of variance (Anova) test at α <0.05 was performed to assess the effectiveness of gradient among soil and plant data. It Observed species richness and diversity indices was performed at habitat type level for both variables using package lawstat of R software (Hui et al., 2008). When requirement of distribution and homogeneity of variance were not met, Kruskal- EcM fungal fruiting started in mid-May and was still Wallis test (Kruskal and Wallis, 1952) was performed in R software. continuing in early October making a cumulative total of Afterward, significant gradient (s) underwent a preliminary analysis 21 weeks of occurrence. In total 2814 fruit bodies have to check collinearity between them and clarify the ordination. One been collected and were sorted into 123 species variable among all highly collinear ones was conserved in the belonging to 23 genera and 09 families (Table 2). The subset of the ordination. That preliminary analysis has been performed with software Statistica 7.1 (StatSoft France, 2006). most frequently recorded family was Russulaceae with 53 species composed of 36 Russula species, 11 Lactifluus species and 6 Lactarius species. The second frequently Ectomycorrhizal fungi fruit bodies spatial distribution observed family was Boletaceae represented by 13 genera with a total of 32 species. The Amanitaceae To visualize the spatial distribution of EFFB, non-metric ranked third most important recorded family with a total of multidimensional scaling NMDS ordination was performed based on a matrix of fungi species relative frequency per plot using function 26 species. The less recorded other families included metaMDS of package Vegan (Oksanen et al., 2015) of R software Cantharellaceae, Cortinariaceae, Gyroporaceae, version 3.3.0 (2016-05-03). Fungi relative frequencies were first Inocybaceae, Sclerodermataceae and Clavulinaceae. transformed by Wisconsin double standardization using function These families were represented each by only one genus Wisconsin to improve ordination. A distance matrix generated by with respectively 1, 3, 1, 1, 5 and 1 species (Figure 2). Bray-Curtis dissimilarity index with function vegdist was used as input for the NMDS whilst function metaMDS used Jaccard index. From the total species richness, 57 taxa (46.34% of the Then, main environment variables (host communities and soil total) were identified up to species level with 19 of them parameters) influencing the fungi communities structure were being related to known species from temperate and evidenced by fitting them the ordination plot using function envﬁt of tropical zones. The remaining 66 species (53.66% of the the Vegan package. Statistical significance was based on 999 total) were identified only at the genus level with some of random permutations and plotting was limited to most significant them suspected new to science (Supplementary Table 1). variables with argument p.max set at 0.1. To better visualize the similarity of habitat types, a hierarchical The most frequent species per habitat type included clustering based on Bray-Curtis dissimilarity index was conducted in Russula congoana Pat. (13 weeks corresponding to the R software version 3.3.0 (2016-05-03) using function hclust and relative frequency of 2.53%), Amanita aff. craseoderma average-linkage. Subsequently, each fungi community was (11 weeks, relative frequency = 2.14%) and Lactarius characterized by conducting indicator species analysis using the tenellus Verbeken & Walleyn (10 weeks, relative MULTIPATT function in the R package Indicspecies (De Cáceres frequency = 1.95%) in IW; Amanita annulatovaginata and Legendre, 2009; De Cáceres and Jansen, 2015). Indicator Value (IndVal) index (Dufrêne and Legendre, 1997) was computed sensu lato Beeli and Lactarius tenellus (both with 8 to measure the association between a species and a site group. weeks, relative frequency = 1.56%) in MW; Cantharellus Statistical significance of association was tested by running 999 addaiensis Henn. and Amanita aff. subviscosa Beeli random permutations. In addition, the specificity (the so-called (both with 11 weeks, relative frequency = 2.14%), IndVal Component A) and the fidelity (second component B of Amanita aff virosa and Amanita strobilaceovolvata sensu IndVal) of a species as indicator of a target site group were inspected. Component A or specificity refers to “the probability that lato Beeli (both in 10 weeks, relative frequency = 1.95%) the surveyed site belongs to the target site group given the fact that in UW. the species has been found” whilst component B refers to “the 22 species were found common to the three habitat Vanié Léabo et al. 33

Figure 2. Families representativeness per habitat type.

types and represented 17.89% of total observed species Weekly-based species accumulation curves of the richness (Supplementary Table 1). On the other hand, 72 different habitat types have almost the same shape in species accounting for 58.53% of the species richness observed and estimated species richness (Figure 3). were specific to one habitat type. Many of these specific Accumulation curves of IW were generally above those of species were observed and collected only once from May the other habitat types through weeks except for the to early October 2014 (Supplementary Table 1) and are estimated species richness where curve of MW outdid uniques species. Specific species such Inocybe sp 1 and the other curves from the fourteenth week till the end of Cortinarius subgenus telamonia sp 1 have been picked the survey. Globally, all curves were ascendant and did under Isoberlinia doka trees in IW. Meanwhile, Russula not reach an asymptote of total richness. annulata R. Heim, R. discopus R. Heim (a rare species) Sample coverage highlighted the percentage of species and Veloporphyrellus africanus Watling were collected detected by our study on the overall estimated species beneath Uapaca togoensis. Final, 29 species (23.58%) richness. Thus, 75.25% of species was detected in IW were shared by two habitat types. In addition with species against 81.88% in MW and 58.78% in UW (Table 3). common to all habitat types, 38 species were shared by Furthermore, 38, 32 and 36 unique species have been IW and MW (e.g. Amanita afrospinosa Pegler & Shah- collected in the different habitat types respectively. Smith, Lactarius saponaceus Verbeken); 28 species shared by IW and UW (e.g. Gyroporus castaneus (Bull.) Quél., Amanita strobilaceovolvata sensu lato) and 29 Habitats characterisation species shared by MW and UW (e.g. Amanita aff. rubescens Pers., Boletus loosii Heinem). Floristic and dendrometric parameters

A cumulative number of 822 stems belonging to 49 Similarity and sampling representativeness woody species with dbh ≥ 10 cm were detected for all habitat types. Those species belonged at least to 20 Computed Simpson's Index of Diversity 1 – D of IW was families, knowing that 6 species identity was 0.97 with an autosimilarity index calculated to 0.40. undetermined. 18, 19 and 31 species were inventoried Therefore, plots in IW were found non-similar likewise for, respectively in IW, MW and UW. The total density and plots within habitat types MW and UW with basal area of all tree species, and the dendrometric respectively0.33 and 0.29. In those latter habitat types, parameters (density and SRD) of cores EcM forest trees higher diversity indices were respectively 0.97 and 0.96. in each plots is provided in Table 4. 34 Int. J. Biodivers. Conserv.

80 a)

40 Isoberlinia Woodland 30 Mixed Woodland Uapaca Woodland

10 Cumulative number of species of number Cumulative

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Frequency of survey b) 120

100

60 Isoberlinia Woodland Mixed Woodland Uapaca Woodland 40

20 Cumulative number of species of number Cumulative 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Frequency of survey

Figure 3. Week-based accumulation curves of observed (a) and estimated (b) species richness of EcM fungi during fruiting season 2014 (mid-May to early- October). Aug. = August, Sept.= September, Oct.= October.

Table 3. Sampling representativeness estimators. Sample coverage: proportion of observed species richness (Sobs) as per cent of estimated species richness (Sest); Auto-similarity: mean similarity between plots of the same habitat type; Uniques: number of species collected only once during the whole period

Habitat Number of Observed species Estimated species Sample Autosim Simpson's Index of Simpson's Uniq type fruit bodies richness Sobs richness Chao 2 (Sest) coverage ilarity Diversity 1- D Evenness ues Isoberlinia 1542 75 99.67 75.25 0.49 0.77 0.06 38 Woodland Mixed 502 65 79.38 81.88 0.41 0.94 0.25 32 Woodland Uapaca 775 56 95.27 58.78 0.36 0.91 0.19 36 Woodland Vanié Léabo et al. 35

Table 4. Mean values of density of woody species, Species relative dominance (SRD) of identified EcM trees and total basal area per habitat.

Plant parameters Isoberlinia Woodland Mixed Woodland Uapaca Woodland Cumulative number of stems (three plots) 276 246 300 Forest tree species richness SR 18 19 31 Total tree density TD (stem/ha) 3066.66 2733.33 3333.33 Total basal area TBA (m2/ha) 179.75 158.43 186.89 Mean canopy cover 66.67 73.33 80 Isoberlinia doka 171.11 5.56 0.00 EcM tree partners density(stem/ha) Monotes kerstingii 35.56 18.89 23.33 Uapaca togoensis 10.00 167.78 153.33 Isoberlinia doka 62.29 3.68 0.00 EcM tree partners SRD (%) Monotes kerstingii 10.28 4.13 6.57 Uapaca togoensis 0.99 53.48 40.50

Table 5. Soil chemical and physical parameters variations per habitat type.

Habitat type Soil parameters F Chi-square Df p-value IW MW UW pH 6.7 ±0.14 6.52±0.4 6.78±0.2 2.0392 2 0.36 Carbon (%) 1.96±0.09 1.85±0.15 1.71±0.13 4.3922 2 0.11 Nitrogen (%) 0.09±0.05 0.09±0.01 0.12±0.02 0.495 2 0.63 Available Phosphorus (ppm) 1.34±0.32 1.63±0.12 1.20±0.12 3.5862 2 0.17 Calcium (cmol/kg) 1.71±0.42 1.45±0.31 1.07±0.17 3.078 2 0.12 Potassium (cmol/kg) 0.06±0.04 0.09±0.03 0.07±0.03 0.936 2 0.44 Clay (%) 8.67±2.08 10±2.64 9.33±0.58 0.85797 2 0.65 FineSilt (%) 9.33±3.51 5±0.00 8.66±3.05 5.7275 2 0.06 CoarSilt (%) 44.33±12.1 42.66±3.05 45.67±5.86 0.29132 2 0.86 FineSand (%) 34.33±8.14 37±2.64 33.67±3.79 1.1954 2 0.55 Type of soil Silt loam Silt loam Silt loam

Kruskal-Wallis test demonstrated that plant richness were generally neutral, ranging from 6.52 to 6.78. As for and total basal area did not differed significantly from one texture analysis, soils in plots were generally silt loamy another habitat type (chi-squared = 1.55, p-value = 0.46 with regard to soil particles size (Table 5). However, and chi-squared = 0.62, p-value = 0.73, respectively). differences among both chemical and physical Considering EcM tree partners, density and SRD of I. parameters of the different habitat types were not doka differed significantly between habitat types (chi- significant at 0.05, pointing out an absence of soil squared = 6.72; p-value = 0.03), IW harboring the highest gradient. values. Density and SRD of U. togoensis were also significant (F = 20.73, p-value = 0.002 and chi-squared = 5.95, p-value = 0.05 respectively), decreasing from MW Ectomycorrhizal fungi fruit bodies spatial distribution to UW and finally IW. At the opposite, the density and SRD of Monotes kerstingii does not significantly differed In absence of soil gradient between habitat types, soil from one another habitat type (chi-squared = 0.62, p- variables were excluded from initial environmental matrix value= 0.73 and chi-squared = 2.51; p-value= 0.28 that was finally reduced to 05 plant variables after respectively). multicollinearity test. Those variables were plant species richness (PlantSp), total basal area (TBA), I. doka density (IDDen), M. kerstingii Density (MKDen) and U. togoensis Soil chemical and physical parameters Density (UTDen). Environment variables fitting into NMDS result pH (H2O) measurement indicated that soils in all plots indicated that I. doka Density (IDDen) and U. togoensis 36 Int. J. Biodivers. Conserv.

Figure 4. EcM fungi distribution at Comoé National Park according to stem density of Uapaca togoensis and Isoberlinia doka.

Figure 5. Hierarchical clustering of permanent plots based of dissimilarity.

density (UTDen) are the main statistically significant plots of habitat 1 (Isoberlinia woodland IW) and the two variables driving the EFFB spatial distribution (Figure 4). first plots of the second habitat, Mixed woodland (MW). UTDen was positively correlated with both axes (r2 = The second group is composed of the remaining plot of 0.92; p-value = 0.002) whilst IDDen was negatively habitat 2 (MW) and all plots of the third habitat Uapaca correlated to the first axis only (r2 = 0.83; p-value = Woodland (UW). The indicator species analysis showed 0.018). that 04 species were significantly associated to just one Hierarchical analysis of study sites evidenced two sites group on a total of 123 species. 03 species were groups (Figure 5). The first group (G1) encompassed all associated to G1 and 01 species to G2 (Table 6). Vanié Léabo et al. 37

Table 6. List of indicator species associated to each site group. Burkina Faso. 126 EcM species were censured after various surveys in different areas of Benin, ranging from Site group Component A Component B Stat p.value protected areas to farms (Yorou, 2010). In Southern Group 1 #sps. 3 Guinea rainforests, Diédhiou et al. (2010) identified 39 RusCon 0.9573 1.0000 0.978 0.013 * EcM fungal taxa. In central Africa, Onguene et al (2012) Pulve1 0.9057 1.0000 0.952 0.028 * reported the collect of 100 EcM fungi in forest habitats of AmaXa 0.8276 1.0000 0.910 0.040 * South Cameroon during a three-year survey. Numerous species have been also collected in Congo and are Group 2 #sps. 1 documented in two series, “Flore Iconographique des AcfVir 1 1 1 0.013 * Champignons du Congo” and “Flore illustrée des Champignons d‟Afrique Centrale”. Highest species Significance codes: 0 „***‟ 0.001 „**‟ 0.01 „*‟ 0.05 „.‟ 0.1 „ ‟ 1 RusCo richness and number of EFFB were found in IW. n: Russula congoana; Pulve1: Pulveroboletus sp 1; AmaXa: Amani ta xanthogala; AcfVir: A. cf virosa According to Nara et al., 2003, such values reflected host development stage. Indeed, highest cumulative values of tree partners‟ stems density and basal area were found in plots of IW. Some of those tree species were estimated DISCUSSION aging more than 200 years with regard to their dbh (Tedersoo, personal communication). In disturbed areas EFFB richness of tropical zones, EcM Fabaceae and Dipterocarpaceae stands (I. doka and M. kerstingii respectively in our case) Mycological monitoring within Comoé National Park are considered climax stands which establishment is (CNP) shed light on very specious habitats where almost facilitated by Uapaca spp. (Lawton, 1978; Högberg and all known EFFB families were represented. As already Piearce, 1986; Onguene, 2000; McGuire, 2007; Tedersoo mentioned in various paleo and neotropical regions et al., 2011; Onguene and Kuyper, 2012). According to (Sanon et al., 1997; Riviere et al., 2007; Bâ et al., 2012; Poilecot et al. (1991), CNP is included of 93.3 % of fire Henkel et al., 2012; Onguene and Kuyper, 2012), climax vegetation from which 6.7 % is made of dominance of Russulaceae and specifically of genus woodlands. Indeed, understorey vegetation in IW and Russula was also observed. Among the other frequently MW were burned either totally or partially according to recruited families in tropical regions, Cantharellaceae plot by the annual fire that passed in December 2013, was represented, in prospected habitats, by only one four months before our arrival at the park. However, no species member of genus Cantharellus, C. addaiensis. In plot in UW was burnt. Moreover, EcM fungi species the contrary, four Cantharellus species (C. floridulus belonging to genus Scleroderma previously described as Heinem., C. platyphyllus Heinem., C. cf. platyphyllus characteristic of disturbed and elevated soil temperature Heinem. and Cantharellus sp.) were reported in areas (Ingleby et al., 1985; Nara et al., 2003) were traditional systems of fallows dominated by many collected within burnt plots of IW and MW. Three of the confirmed EcM tree partners near the city of Korhogo five Scleroderma species were recruited in IW and the North western part of Côte d‟Ivoire (Ducousso et al., latter two in MW. Consequently, IW is likely older than the 1999). This difference may be due to higher number of others whilst UW is the youngest and MW at an tree partners in that area, namely Afzelia Africana Sm. ex intermediate stage. This assumption is strengthened by Pers., Anthonotha crassifolia (Baill.) J. Léonard, Berlinia the different proportions of U. togoensis and grandiflora (Vahl) Hutch. & Dalziel, I. doka and U. presence/absence of I. doka in the different habitats. togoensis. Likewise in genus Clavulina, only one species First, IW harboured many stems of the EcM tree partners was detected in Isoberlinia woodland (IW) suggesting Monotes kerstingii Gilg and Uapaca togoensis but it is that other species may have been overlooked or mistook dominated by Isoberlinia doka. Second, few stems of I. for saprotrophic species. Few species belonging to doka were censured in MW whilst the tree species is genera Inocybe and Cortinarius were also found in CNP. completely absent from UW plots. Another support of that This supports the trend observed in other tropical regions assumption is the presence of Inocybe sp. and the (Onguene and Kuyper, 2002; Riviere et al., 2007; number of species of genus Cortinarius in IW are other Onguene and Kuyper, 2012), and strengthens the idea supports of that assumption since those EcM fungi were that those species might be adapted to temperate and depicted late successional symbionts (Nara et al., 2003). boreal zones (Buyck et al., 1996). However, the paucity of studies in tropical woodlands and forests comparative to temperate and boreal ones should be considered. Yet, Sampling representativeness the abundance of EcM fungi species was highlighted at continental level. In West Africa, Sanon et al (1997) found Sampling representativeness assessment demonstrated 37 EcM fungi during rainy season 1994 and 1995 in that a large number of symbiotic fungi were not detected savanna and open riparian forests in southwestern in the different habitats monitored. This result is 38 Int. J. Biodivers. Conserv.

corroborated by the important values of uniques species EFFB species fruited and were collected. Their that reflected rare species. That number of observed rare abundance and spatial distribution were significantly species give an estimate of the number of unseen correlated to the stem density of U. togoensis and I. doka species (Chiarucci et al., 2011) as captured by the that were respectively the dominant species in each site estimated species richness in each habitat. That result is group. R. congoana, Pulveroboletus sp 1 and A. a support of the limitation of fruit body based study of xanthogala were good indicators of site group G1 and A. EcM fungi species (Horton and Bruns, 2001; Taylor, cf virosa for G2. However, further studies on contrasting 2002). Nevertheless, climate impact is more appreciable soil types, fungal and forest succession, site microclimate on fruit bodies than on below-ground tips (Andrew and as well as fire impact are needed to improve the Lilleskov, 2009; Pickles et al., 2012). understanding of fungal community dynamics in West African woodlands.

Spatial distribution of symbiotic fungi Conflict of Interests Phytosociological study of permanent plots evidenced important floristic richness and especially numerous The authors have not declared any conflict of interests. stems with dbh above 10 cm. EcM tree partners thrive in dominant and sometimes almost mono-dominant stands. Such habitats have been demonstrated as niche for ACKNOWLEDGEMENTS abundant EcM fungi. I. doka and U. togoensis were the main dominant species in prospected habitats. Sites This work was funded by the German Federal Ministry of grouping were correlated with their density more than Education and Research (BMBF) through the West stands age. Indeed, though only stems with dbh above African Science Service Centre on Climate Change and 10 cm were considered in data analysis, numerous Adapted Land Use (WASCAL, www.wascal.org) initiative. juveniles and sprouts were present within plots. This was The authors gratefully acknowledge the helpful favorable to the establishment of both early- and late- assistance of master students Bakari Soro and Guillaume successional EcM fungi. In addition, the grouping also K. L. Kra during field work. They acknowledge also the reflected fire impact within study sites evidencing the technical assistance of Laboratoire Central de “drought-tolerant” capacity of some collected fungi Biotechnologie of the Centre National de Recherches species. There is therefore an urgent need to monitor Agronomiques CNRA (Côte d‟Ivoire), the Laboratory of such disturbed stands to adequately address that Systematic Mycology of Ludwig-Maximilians-University assumed capacity. LMU Munich (Germany) and the Botanical Garden Meise Indicator species analysis evidenced four species (Belgium). They are also grateful to Drs. Souleymane associated to site groups (three species associated with Konaté, Kanvaly Dosso and Edson Bomisso for their G1 and one species with G2). Those species, Russula invaluable advices. The authors also thank the two congoana, Pulveroboletus sp 1 and A. xanthogala were anonymous reviewers for their comments to improve the good indicators of G1 and A. cf virosa was for G2 taking manuscript. into account specificity and fidelity. Indeed, those species were collected either exclusively in plots assigned to REFERENCES each group or predominantly in them. Association of R. congoana and A. xanthogala to I. doka was also AFNOR (1995). NF ISO 10694 (X31-409). Soil quality- Determination of documented in Benin by De Kesel et al. (2002). Those organic and total carbon after dry combustion (elementary analysis). species are mentioned in literature as edible fungi in French norm AFNOR. AFNOR (1999). NFX 31-130 soil quality. Chemical methods, various part of Africa (Boa, 2004). As for the two Determination of Cation Exchange Capacity (CEC) and Cation remaining indicators species, they need to be Extraction, AFNOR, Paris. characterised and compared to available monographs AFNOR (2003). NFX 31-107 standard. Qualité du sol. Détermination de and / or keys to ascertain their identity at species level. la distribution granulométrique des particules du sol. Méthode à la pipette. AFNOR, Paris. However, they are likely associated to U. togoensis. Andrew C, Lilleskov EA (2009). Productivity and community structure of Arbonnier M (2004). Trees, shrubs and lianas of West African dry zones. Margraf Publishers. Conclusion Bâ AM, Duponnois R, Moyersoen B, Diédhiou AG, (2012). Ectomycorrhizal symbiosis of tropical African trees. Mycorrhiza. Springer-Verlag. A six-month monitoring of EFFB ascertained their Bahram M, Põlme S, Kõljalg U, Zarre S, Tedersoo L (2012). Regional occurrence at Comoé National Reserve in the Sudanian and local patterns of ectomycorrhizal fungal diversity and community climatic zone of Côte d‟Ivoire. Woodlands of the reserve structure along an altitudinal gradient in the Hyrcanian forests of harboured high plant species diversity from which known northern Iran. New Phytol. 193(2):465-473. Beeli M (1935). Amanita, Volvaria. Flore Iconographique des EcM tree partners were frequently dominant. In these Champignons du Congo, 1:1-28. habitat types estimated of more than 200 years old, 123 Boa ER (2004). Wild edible fungi: a global overview of their use and Vanié Léabo et al. 39

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Vanié Léabo et al. 41

SUPPLEMENTARY DATA

Table 1. Relative frequency of occurrence of EcM fungi species within woodlands of Comoé National Park.

Distribution class Taxon Family IW MW UW Amanita aff. subviscosa Amanitaceae 1.56 0.58 2.14 Amanita annulatovaginata sensu lato Amanitaceae 0.58 1.56 0.39 Amanita sp 13 Amanitaceae 1.17 0.78 0.78 Amanita xanthogala Amanitaceae 0.39 0.19 0.19 Cantharellus addaiensis Cantharellaceae 1.75 0.97 2.14 Cortinarius sp 1 Cortinariaceae 0.19 0.19 0.39 Lactifluus aff. emergens Russulaceae 0.78 0.19 0.39 Lactifluus luteopus Russulaceae 0.19 0.78 1.56 Phylloporus ampliporus Boletaceae 0.39 0.58 0.19 Pulveroboletus sp 1 Boletaceae 1.17 0.39 0.19 Pulveroboletus sp 2 Boletaceae 0.58 0.78 1.36 Common to all habitat types Russula aff. cellulata Russulaceae 0.39 0.19 0.58 Russula aff. ochrocephala Russulaceae 0.58 0.78 0.97 Russula cellulata Russulaceae 0.78 0.58 0.39 Russula cf amoenolens Russulaceae 0.78 0.39 0.58 Russula cf flavobrunnea Russulaceae 0.97 0.39 0.58 Russula cf grisea Russulaceae 0.19 0.19 0.19 Russula ciliata Russulaceae 0.19 0.39 0.19 Russula congoana Russulaceae 2.53 0.78 0.19 Russula sp 10 Russulaceae 0.58 0.19 0.78 Russula sp 11 Russulaceae 0.19 0.19 0.39 Xerocomus sp 4 Boletaceae 0.19 0.19 0.19

Amanita congolensis Amanitaceae 0.00 0.78 0.97 Amanita sp 12 Amanitaceae 0.19 0.39 0.00 Amanita aff. virosa Amanitaceae 0.00 1.36 1.95 Amanita masasiensis Amanitaceae 0.19 0.19 0.00 Amanita sect lepidella sp 1 Amanitaceae 0.39 0.19 0.00 Amanita sect. lepidella strips xanthogala sp 1 Amanitaceae 0.19 0.00 0.19 Amanita sp 5 Amanitaceae 0.19 0.19 0.00 Amanita sp 8 Amanitaceae 0.19 0.00 0.39 Amanita strobilaceo-volvata sensu lato Amanitaceae 0.58 0.00 1.95 Boletus loosii Boletaceae 0.00 0.97 0.78 Boletus sp 2 Boletaceae 0.39 0.00 0.58 Gyroporus castaneus Gyroporaceae 0.19 0.00 0.58 Shared by two habitat types Lactarius afroscrobiculatus Russulaceae 0.00 0.19 0.39 Lactarius saponaceus Russulaceae 0.19 0.19 0.00 Lactarius tenellus Russulaceae 1.95 1.56 0.00 Lactifluus aff. heimii Russulaceae 0.97 0.19 0.00 Lactifluus sp 4 Russulaceae 0.19 0.19 0.00 Octaviana ivoryana Boletaceae 1.17 0.19 0.00 Rubinoboletus cf balloui Boletaceae 0.00 1.17 0.19 Rubinoboletus cf griseus Boletaceae 0.39 0.39 0.00 Russula cf sesenagula Russulaceae 0.58 0.39 0.00 Russula sect griseineae Russulaceae 0.00 0.19 0.19 Russula sect. archaeina Russulaceae 0.39 0.19 0.00 Russula sp 7 Russulaceae 0.19 0.19 0.00 Scleroderma sp 2 Sclerodermataceae 0.58 0.19 0.00 Sutorius sp 1 Boletaceae 0.39 0.00 0.39 42 Int. J. Biodivers. Conserv.

Table 1. Contd.

Tylopilus sp 1 Boletaceae 0.00 0.19 0.39 Xerocomus subspinulosus Boletaceae 0.39 0.39 0.00

Amanita aff. craseoderma Amanitaceae 2.14 0.00 0.00 Amanita cf crassiconus Amanitaceae 0.00 0.97 0.00 Amanita sp 1 Amanitaceae 0.19 0.00 0.00 Amanita sp 2 Amanitaceae 0.00 0.19 0.00 Amanita sp 3 Amanitaceae 0.19 0.00 0.00 Amanita sp 4 Amanitaceae 0.00 0.00 0.19 Amanita sp 6 Amanitaceae 0.19 0.00 0.00 Amanita sp 7 Amanitaceae 1.75 0.00 0.00 Amanita sp 9 Amanitaceae 0.19 0.00 0.00 Amanita sp 10 Amanitaceae 0.19 0.00 0.00 Amanita sp 11 Amanitaceae 0.19 0.00 0.00 Amanita subviscosa Amanitaceae 0.39 0.00 0.00 Boletellus linderi Boletaceae 0.97 0.00 0.00 Boletellus longipes Boletaceae 0.00 0.58 0.00 Boletus pallidisimus Boletaceae 0.00 0.19 0.00 Boletus sp 1 Boletaceae 0.00 0.00 0.19 Clavunila sp 1 Clavulinaceae 0.19 0.00 0.00 Cortinarius aff violaceus Cortinariaceae 0.39 0.00 0.00 Cortinarius subgenus telamonia sp 1 Cortinariaceae 0.58 0.00 0.00 Inocybe sp 1 Inocybaceae 0.58 0.00 0.00 Lactarius sp 1 Russulaceae 0.00 0.00 0.19 Lactarius sp 2 Russulaceae 0.00 0.00 0.19 Specific to one habitat type Lactarius sp 3 Russulaceae 0.00 0.39 0.00 Lactifluus flammans Russulaceae 0.00 0.39 0.00 Lactifluus gymnocarpoides Russulaceae 0.00 0.00 0.19 Lactifluus pelliculatus Russulaceae 0.00 0.00 0.97 Lactifluus sp 1 Russulaceae 0.00 0.19 0.00 Lactifluus sp 2 Russulaceae 0.00 0.00 0.19 Lactifluus sp 3 Russulaceae 0.19 0.00 0.00 Lactifluus volemoides Russulaceae 0.00 0.39 0.00 Phylloporus cf rhodophaeus Boletaceae 0.58 0.00 0.00 Porphyrellus sp 1 Boletaceae 0.19 0.00 0.00 Pulveroboletus sp 3 Boletaceae 0.00 0.00 0.58 Russula aff. flavobrunnea Russulaceae 0.19 0.00 0.00 russula cf annulata Russulaceae 0.00 0.00 0.39 Russula cf mairei Russulaceae 0.00 0.39 0.00 Russula cf ochrocephala Russulaceae 0.39 0.00 0.00 Russula cf subfistulosa Russulaceae 0.00 0.00 0.39 Russula discopus Russulaceae 0.00 0.00 0.19 Russula oleifera Russulaceae 0.00 0.19 0.00 Russula sp 1 Russulaceae 0.00 0.19 0.00 Russula sp 2 Russulaceae 0.00 0.19 0.00 Russula sp 3 Russulaceae 0.19 0.00 0.00 Russula sp 4 Russulaceae 0.39 0.00 0.00 Russula sp 5 Russulaceae 0.00 0.19 0.00 Russula sp 6 Russulaceae 0.00 0.00 0.19 Russula sp 8 Russulaceae 0.00 0.00 0.19 Russula sp 9 Russulaceae 0.19 0.00 0.00 Russula sp 12 Russulaceae 0.19 0.00 0.00 Vanié Léabo et al. 43

Table 1. Contd.

Russula sp 13 Russulaceae 0.00 0.19 0.00 Russula sp 14 Russulaceae 0.00 0.00 0.19 Russula sp 15 Russulaceae 0.00 0.00 0.19 Russula sp 16 Russulaceae 0.58 0.00 0.00 Russula sp 17 Russulaceae 0.19 0.00 0.00 Russula sp 18 Russulaceae 0.00 0.00 0.19 Scleroderma cf cepa Sclerodermataceae 0.58 0.00 0.00 Scleroderma cf citrinum Sclerodermataceae 0.00 0.19 0.00 Scleroderma sp 1 Sclerodermataceae 0.00 0.58 0.00 Scleroderma aff. verrucosum Sclerodermataceae 0.19 0.00 0.00 Tubosaeta heterosetosa Boletaceae 0.39 0.00 0.00 Tylopilus griseus Boletaceae 0.00 0.00 0.19

Tylopilus niger Boletaceae 0.39 0.00 0.00 Boletoid sp 1 Boletaceae 0.00 0.00 0.19 Tylopilus sp 2 Boletaceae 0.00 0.58 0.00 Tylopilus sect. chromapes sp 1 Boletaceae 0.00 0.00 0.19 Veloporphyrellus africanus Boletaceae 0.00 0.00 0.97 Xerocomus sp 1 Boletaceae 0.00 0.19 0.00 Xerocomus sp 2 Boletaceae 0.00 0.00 0.19 Xerocomus sp 3 Boletaceae 0.19 0.00 0.00 Xerocomus sp 5 Boletaceae 0.00 0.19 0.00 Xerocomus sp 6 Boletaceae 0.78 0.00 0.00 Xerocomus sp 7 Boletaceae 0.00 0.19 0.00

IW: Isoberlinia Woodlands; MW: mixed wwoodlands: UW: Uapaca Woodlands.

1b 1a1a 1b1b

Figure 1a, b. Russula congoana.

2a 2b2b 2a 2b 2a 2b Fig.Fig. 1a, 1a, 1b: 1b: Russula Russula congoanacongoana;; fig.fig. 2a, 2b: Amanita xanthogalaxanthogala

Fig.Fig. 1a,1a, 1b:1b: RussulaRussula congoana; fig. 2a, 2b:2b: Amanita xanthogalaxanthogala

44 Int. J. Biodivers. Conserv. 1b 1a1a 1b1b

2a 2b2b 2a 2b 2a 2b Fig.Fig. 1a, 1a, 1b: 1b: Russula Russula congoanacongoana;; fig.fig. 2a, 2b: Amanita xanthogalaxanthogala

Fig. Fig. 1a,1a, 1b:1b: RussulaRussula congoana; fig. 2a, 2b:2b: Amanita xanthogalaxanthogala Figure 2a, b. Amanita xanthogala.

Figure 3a, b. Pulveroboletus sp 1.

Fig. 3a, 3b: Pulveroboletus sp 1; fig. 4a, 4b: Amanita cf virosa

Fig.Figure 3a, 3b: 4a, Pulveroboletus b. Amanita sp cf 1; virosa. fig. 4a, 4b: Amanita cf virosa

Vol. 9(2), pp. 45-55, February 2017 DOI: 10.5897/IJBC2016.0976 Article Number: 4699BE962717 International Journal of Biodiversity ISSN 2141-243X Copyright © 2017 and Conservation Author(s) retain the copyright of this article http://www.academicjournals.org/IJBC

Full Length Research Paper

The attitudes and practices of local people towards wildlife in Chebera Churchura national park, Ethiopia

Aberham Megaze1*, Mundanthra Balakrishnan2 and Gurja Belay2

1Department of Biology, Faculty of Natural Sciences, Wolaita Sodo University, P. O. Box 138 Wolaita Sodo, Ethiopia. 2Department of Zoological Sciences, Addis Ababa University, P. O. Box 1176, Addis Ababa University, Ethiopia.

Received 12 April, 2016; Accepted 29 November, 2016

Human activities that affect wildlife and their habitats are pervasive and increasing. Understanding the effects of humans on wildlife populations, as well as devising strategies to ameliorate these effects, is an increasing challenge for resource managers. Commitment of local communities to protected areas is also essential for conserving biodiversity, but little is known about local people attitudes toward biodiversity conservation. Therefore, this paper provides an empirical assessment of local people activities and their attitudes that affect wildlife and their habitats around Chebera Churchura National Park, Ethiopia from 2012 to 2014. Nine villages around the park were selected for this study. A total of 354 households were selected randomly for interview. A semi-structured questionnaire survey, focus group discussions and direct field observations were carried out in the nine selected villages. Among the various human activities recorded, firewood collection, bushfires setting fire, hunting, livestock grazing and farming were having great impacts on biodiversity conservation in the Park. Among the respondents, 51.2% reportedly used the park for livestock grazing, 50.2% for firewood and fodder collection, 15.6% for wild honey and spices collection, 23.1% for timber, 2.6% for wild meat and 2% for farming in and along the boundaries of the Park. Most respondents had positive attitudes towards the conservation of wildlife. A combined strategy aimed at improving local participation in wildlife conservation initiatives, initiation of public education and awareness campaigns and provision of alternative sources of income for the local people will reduce the threat, and contribute to improve conservation of wildlife in Chebera Churchura National Park.

Key words: Human activities, resource use, wildlife conservation.

INTRODUCTION

Throughout history, human factors have been major pronounced in developing countries, which are more drivers of biodiversity loss (Hackel, 1999). Ninety-nine dependent on natural resources as their primary source percent of the IUCN Red List species are threatened by of income (Wilfred, 2010). In developing countries, these factors (IUCN, 2003). Biodiversity loss is more pressure on natural resources is growing in tandem

*Corresponding author. E-mail: [email protected].

Author(s) agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License 46 Int. J. Biodivers. Conserv.

with rapidly growing human populations (Oladeji et al., vation measures cannot be achieved successfully without 2012). Wildlife species, which are important to humans, clear information about the impact of human activities on decline or disappear as wildlife habitat is cleared for conservation of wildlife. Therefore, this study aimed to anthropogenic activities (Oladeji et al., 2012). Habitat loss investigate the potential impact of various human and fragmentation affect the survival of wildlife in various activities and their attitudes on conservation of wildlife in ways including influencing the behavior, abundance, the CCNP, and to obtain useful information to enable distribution of animals, as well as reducing the extent of recommendations to be made regarding better usable habitats and degrading habitat quality (Masanja, management of the Park. 2014). In developing nations, firewood remains the major source of energy for cooking, heating and lighting. Until 2010, around 2.8 billion people mainly in developing MATERIALS AND METHODS nations relied on traditional use of biomass for cooking Study area and heating (Bonjour et al., 2013). The over utilization of wood products by rural human communities aggravates Chebera Churchura National Park (6°39′-7°09′N and 36°27′-36°57′ E) is located 580 km south- west of Addis Ababa (Figure 1). It the degradation of the habitats of wildlife, and is the 2 major threat to protected areas in developing countries covers an area of 1,215 km , and lies within the western side of the Central Omo Gibe Basin. The mean annual rainfall of the area is today (Masanja, 2014). Wildfire is a common 2,154 mm. There are two main seasons, the dry season from phenomenon across the African continent (Archibald et December to February and the wet season from March to al., 2012). Humans are regarded as the main source of November. Four main rivers and their tributaries drain the area. The wildfire globally, accounting for 59 to 95% of ignitions area is rich in floral and faunal biodiversity, consisting of 37 species (FAO, 2007). Studies from east, west, and southern of large mammals, 18 species of small mammals and 137 bird species (Demeke and Afework, 2013). Africa reported that burning protected areas was mostly for livelihood-related, notably range management, thatch production, predator-cover reduction, gathering, hunting Methods and agricultural production (Gandiwa et al., 2014). Agriculture remains a predominant livelihood activity in The present study was carried out through a questionnaire survey and focus group discussions (Newmark et al., 1994; Maddox, most parts of Africa (Coad, 2007; Gundogdu, 2011). In 2003), to collect primary data among the households in the study Ethiopia, expansion of agricultural practices, settlement area. The questionnaire had both open and close ended questions and increasing pressure of human and livestock to get information about anthropogenic activities in the study area. It populations are major threats in several protected areas was also supplemented with field observations of various aspects of (Tadesse and Kotler, 2013). Local communities' resource use, benefits from wildlife and the associated costs. A preliminary survey was conducted in August, 2012 prior to the perceptions of protected areas influence the kinds of actual data collection period. This helped to (i) identify the interactions people have with them, and thereby boundaries of the park, (ii) decide the number of villages/sites conservation effectiveness (Ramakrishnan, 2007). Their based on purposive sampling method and (iii) have a general perceptions of protected areas management play also an understanding of the overall situations like anthropogenic activities important role in their attitudes toward them (Anthony, and problems related to crop damage and livestock loss in CCNP. 2007). Therefore, understanding residents' perceptions The questionnaire was pre-tested on randomly selected 62 individuals of varying age, sex and social economic activities about conservation is the key to improve the protected among the local communities. These individuals were not included areas-people relationship if protected areas are to in the main sample group. This helped to identify the various achieve their goals (Weladji et al., 2003). Many factors anthropogenic activities in the area and to modify the questionnaire influence the perceptions of the protected areas held by accordingly. Nine villages from 25 Peasant Associations were residents living in their periphery. These include the selected based on the information gathered using the preliminary history of park management, the degree of awareness of survey: (i) the distance from the Park, (ii) problems related to crop damage and livestock loss, (iii) dependence of local people on the protected areas existence, the education level, the Park and (iv) encroachment within the Park area. A total of 354 reference to future generation (Bauer, 2003) and the households were selected randomly for the interview. The age of gender and ethnicity (Mehta and Heinen, 2001). The participants ranged from 18 to 72 years. The questionnaire was understanding of all these factors is important to improve administered to all households, of which 230 (65%) were males and the relationship between local residents and protected 124 (35%) were females. Interview questions were written in English, but all interviews were translated and conducted in Dawuro areas and will improve people awareness about local language to reduce misunderstandings during the interviews, biodiversity conservation within these areas. Therefore, due to cultural and language differences, through back-translation collecting baseline information on various human of the interview script (Müller, 2007). Eighteen local people, activities and their attitudes is a vital step in managing the consisting of two residents in each of the 9 study village were impact of human activities on biodiversity conservation. recruited and trained to administer the questionnaires. Chebera Churchura National Park (CCNP) in Ethiopia is To ensure accuracy, the same translators were used and the same interview questions. The questionnaire was administered to a conservation area where the impact of human activities farmers within their area of farming and/or residence (Hill, 2000), at on conservation of wildlife has not been studied as is the a random manner based on first come, first-serve basis (Newmark case in many other parts of Ethiopia. Effective conser- et al., 1994), and alternating male and female respondents as Megaze et al. 47

Figure 1. Location map of the study area.

much as possible and different age groups. In some households, interest. These include: (i) demographic data and (ii) various the head was interviewed and other people present in a house anthropogenic activities (grazing, wildfire setting, hunting, firewood usually helped in the recall. Respondents answered each attitudes gathering, agricultural activities and other socio- economic statement according to their strength of agreement by the following activities, which could have negative impacts on wildlife in the attitudes level scores: 1= for strongly agree, 2=agree, 3= neutral, area). Data were collected using a semi-structured survey design, 4= disagree, and 5= strongly disagree (Likert, 1974). The villages following a similar format used by Maddox (2003). Data were covered were Chebera, Serri, Dalba, Yore, Shita, Churchura, analyzed using SPSS computer software version 20 (SPSS Inc, IL, Chewda, Gudumu and Adabachew, ranging from 0 to 5 km apart U-S-A). Appropriate statistical methods such descriptive statistics from the boundary of the Park. The questionnaire consisted of a and frequency were used to analyse the data. To test for the mean series of semi-structured questions focusing on two main areas of differences in attitude toward conservation of biodiversity among 48 Int. J. Biodivers. Conserv.

Table 1. Socio-demographic profile of the respondents and their attitude towards CCNP.

Parameter Attitude towards the conservation area (%) Category Variables Number of respondents % Positive% Negative% No idea% Male 230 65 63.0 30.5 6.5 Gender Female 124 35 39.6 41.8 18.6

≥18 29 8.2 69.7 27.4 2.9 20−29 55 15.5 63.9 30.2 5.9 30−39 85 24 60.5 33.4 6.1 Age group 40−49 104 29.4 57.9 35.5 6.6 50−59 53 15 53.8 39.3 6.9 >59 28 7.9 50.7 40.4 8.9

Illiterate 194 54.8 44.5 50.1 5.4 Primary level 96 27.1 60.2 33.8 6.1 education Education Secondary 28 7.9 71.4 23.3 5.3 level education Informal 36 10.2 45.5 47.1 7.4 education

Married 286 80.8 61.2 33.2 5.6 Single 20 5.6 70.2 25.3 4.5 Marital status Divorced 37 10.5 45.3 51.2 3.5 Widowed 11 3.1 39.5 55.6 4.9

1−3 123 36.8 49.5 45.3 5.2 4−6 200 60 34.7 59.3 6.0 Family size 7−10 8 2.3 30.2 64.3 5.5 >10 3 0.9 31.6 65.0 3.4

age groups and gender of the respondents, a non parametric test triangulated through questionnaire interviews, focus group was conducted on all the test variables. Spearman rho was used to discussions and field observations. evaluate the correlation among the attitudes of the respondents toward the conservation area.

RESULTS Focus group discussion Socio-demographic characteristics Focus group discussions method was used to reinforce the data collected through the questionnaire. Group discussions were organized to obtain direct first-hand information through The socio-demographic characteristics (sex, age-groups, spontaneous responses from the respondent, and the discussions religious groups, occupation and educational background) solicited information about local community attitudes of biodiversity of the respondents living in the communities surrounding conservation. Two focus group discussions sessions were CCNP are presented in Table 1. Out of the 354 conducted in each of the study village, and the group size in each respondents, 65% were males and 35.02% females. The discussion site varied from 15 to 21. The participants were invited to youngest respondent was 18 years old, and the oldest 72 discuss issues according to their convenience. Park staffs, village leaders, local elders, primary school teacher in the village, other years. Majority (68.9%) of the respondents were between government employers and students have participated to discuss 29-49 years old, while 8.1 and 7.9% of the respondents their experience concerned with conservation and to gather their were less than 20 years and older than 59 years old, information on wildlife in the area. During such group discussions, respectively. Most of the respondents (80.8%) were the researcher initiated the discussion by stating some of the married, 5.6% were single, 10.5% divorced and 3.1% observations and responses from people interviewed and from questionnaires. Information collected from group discussions were were widowed. Most of the respondents (54.8%) were collated and summarized using text analysis method, and presented illiterate, 10.2% had informal education, 27.1% had in a narrative fashion. Thus, the information acquired was primary education, 7.9% had secondary education and Megaze et al. 49

Table 2. Percentage of resource utilization by the respondents of different villagers in Chebera Churchura National Park.

Respondents (%) involved in different activities CF LG FW & FC WH & SC WM TC OT Village n (354) % % % % % % % Chebera 48 0.5 51.5 58.5 5.7 2.1 20 0 Sirri 21 4.3 53.4 52.9 21.3 1.2 25.5 0.2 Dalba 44 0.1 50.0 49.5 16.3 1.5 30.3 0.0 Yora 42 2.4 55.7 46.6 12.4 2.1 32.5 0.1 Shita 39 1.4 52.9 48.7 4.5 1.3 27.5 7.3 Churchura 48 3.2 57.5 56.8 26.2 5.6 25.4 1.7 Chewda 34 2.1 45.3 43.6 17.3 2.4 13.5 0.5 Gudumu 48 2.2 48.9 46.9 15.8 5.9 17.8 0.4 Adabacho 30 1.9 45.7 47.9 20.5 1.7 15.3 0.3 Mean 2.0 51.2 50.2 15.6 2.6 23.1 1.2

CF= Crop farming, LG= Livestock grazing access, FW & FC= Firewood gathering, fodder collection and thatching houses, WH & SC= Wild honey and spices collection, WM= Wildmeat access, TC= Timber collection for different purpose, OT= Other benefits.

none had gone beyond secondary level education. There boundaries of the Park. were significant differences in the educational status among the respondents (χ2 = 98.16, df =3, P<0.05). The majority of respondents (55.4%) had positive attitudes Livestock grazing towards the conservation area, while 38.6% had negative attitudes. Most of the better-educated groups (65.8%) Majority of the livestock of the respondents (82.3%) had positive attitudes than less-educated respondents grazed inside and around the Park, 39.0% inside the (45%), the difference were significant (χ2= 27.5, df =3, Park and 43.3% in the buffer zone of the Park. Only P<0.05). Most (60%) of the respondents had 4 to 6 family 17.6% of the local people have own grazing land. The members. On the other hand, 36.8, 2.3 and 0.9% of the villages differed significantly (χ2 = 48.34, df =8, P<0.05) respondents had 1 to 3, 7 to 10 and > 10 family regarding livestock grazing in the study area (Table 3). members, respectively (Table 1). Respondents with large family size had more negative attitudes towards the conservation area than those with small family size. Firewood and timber extraction Mixed farming (crop cultivation and livestock rearing) was the main means of livelihood of most of the respondents The main source of energy for the people around CCNP (76.8%) in CCNP, and only 12.7% depend on crop was firewood. Among the respondents, 35.9% collected farming. Among the respondents, 10.4% claimed to have firewood and construction materials from the interior of been involved in one or more secondary occupations. the park, 54.4% from the buffer zone, and 9.6% from The majority of respondents (51.1%) had a positive other sources like the farm area (Figure 2). attitude towards the conservation area, but on an average 40.5% had negative attitude. The major livestock reared by the local communities are cattle (44.7%), goat Illegal hunting (17.1%), sheep (16.4%) and pack animals including donkeys (17.1%), mules (7.6%) and horses (6.9%) in Majority of the respondents (80.43%) indicated that it was nine villages surrounding the park. easy to obtain wild meat in the locality, while the remaining 19.57% stated that it was not easy. The difference was significant (χ2 = 49.85, df =1, P<0.05). Resource utilization Most respondents across the nine study villages reported that illegal hunters commonly used wire snaring (54.8%) Local communities are dependent on a number of natural and firearms (45.5%). The least reported illegal hunting resources in the Park for their livelihoods (Table 2). methods were poisoning (1.24%), hunting with dogs Majority of the respondents acknowledged getting benefits (0.17%) and fire (0.12%) (Table 4). Poisoning, mostly from the Park, 51.2% using the conservation area for using herbicides and pesticides, was used in retaliate livestock grazing, 50.2% for firewood and fodder against large carnivores such as spotted hyena and lion collection, 15.6% for wild honey and spices collection, as a way to reduce livestock–carnivore conflicts. Wildfire 23.1% for timber collection and 2% for farming along the was used to drive animals towards snares and to make 50 Int. J. Biodivers. Conserv.

Table 3. Grazing sites of villagers in Chebera Churchura National Park.

Livestock grazing (%) Village n (354) Distance from the Park (km) In the Park % In the buffer zone % Own grazing land % Chebera 48 1–2 41.5 52.4 6.51 Sirri 21 0–2 39.3 48.9 11.7 Dalba 44 3–5 40.5 45.8 13.7 Yora 42 0–2 44.4 43.8 11.7 Shita 39 3–5 37.4 38.9 23.6 Churchura 48 1–3 45.6 47.5 6.8 Chewda 34 0–2 36.9 37.7 25.4 Gudumu 48 2–3 32.0 34.6 33.4 Adabacho 30 2–4 33.4 40.4 25.9

Figure 2. Different sites of fire wood and timber collection by the respondents.

hunting by dogs easier. A total of 22 wildlife species, (Panthera pardus) (10%), lion (Panthera leo) (8%) and including large herbivores and carnivores were reported black-backed jackal (Canis mesomelas) (2%) were also to be illegally killed in the CCNP ecosystem. Most of the illegally killed in the CCNP ecosystem (Figure 3). The respondents reported that African buffalo (Syncerus respondents highlighted five reasons for illegal hunting of caffer) (71%), African elephant (Loxodonta africana) wild animals: (i) source of protein for domestic (45%), common warthog (Phacochoerus africanus) consumption (40.4%), (ii) reduction of crop damage and (33%), waterbuck (Kobus ellipsiprymnus) (25%) and livestock predation (47.9%), (iii) sale to enhance income bushbuck (Tragelaphus scriptus) (21%) were the most (25.5%), (iv) reduction of threats to humans (21.7%), (v) abundant, preferred and commonly hunted animals. use for traditional/cultural ceremonies (2.0%). The In addition, Anubis baboon (Papio anubis) (34%), difference were significant (χ2= 59.98, df =8, P<0.05). spotted hyena (Crocuta crocuta) (11%), leopard Across the nine study villages, the differences in Megaze et al. 51

Table 4. Percentage of illegal hunting methods among different villages in Chebera Churchura National Park area

Common illegal hunting methods (%) Villages Snares Firearms Poisoning Wildfire Hunting with dogs Chebera 69.4 26.4 3.6 0.5 0.3 Sirri 56.9 40.7 2.2 0.2 0.1 Dalba 58.7 47.8 1.7 0.1 0.2 Yora 56.5 48.0 0.2 0.0 0.0 Shita 53.8 45.7 0.4 0.0 0.0 Churchura 39.3 61.5 2.1 0.3 0.3 Chewda 54.7 45.2 0.0 0.0 0.0 Gudumu 55.1 44.5 0.0 0.0 0.4 Adabacho 48.7 49.8 1.0 0.0 0.2 Mean 54.8 45.5 1.24 0.12 0.17

(Total percentage exceeds 100 for each ward because the respondents were allowed to give multiple answers).

Figure 3. Percentage of wild animals hunted in Chebera Churchura National Park area.

perceptions of respondents concerning illegal hunting in Wildfire the CCNP ecosystem during 2012 to 2014 were significant (χ2= 51.23, df =8, P<0.05). Of the respondents, Most of the respondents (97.9%) stated that wildfires 61.6% thought illegal hunting activities had decreased, were of anthropogenic origin, 88.7% of the fires being 20.8% indicate that it had increased, and only 17.5% deliberately set by the local people, largely hunters thought there had been no change. The main reasons (83.5%) or farmers (16.5%) to clearing vegetation for given for the perceived decline of illegal hunting in the cultivation. CCNP ecosystem were: (i) fear of arrest and Accidental wildfires resulted from collection of wild imprisonment (73.1%), (ii) strengthened law enforcement honey (76.6%) and cooking on farms (23.2%). Most of operations (40.3%), (iii) fear of Park Rangers (22.2%), the farmer-respondents set fires once a year, usually and (iv) lack of firearms to use in illegal hunting (17.9%). during the dry season (December to February). 52 Int. J. Biodivers. Conserv.

Illegal farming conservation (Mishra et al., 2003). Findings of this investigation also indicated that respondents who were The local communities surrounding the CCNP had been educated had more positive attitude towards using the Park area for agricultural purposes even before conservation than those with less or no education. In the the establishment of the Park, especially the communities study area, the younger residents tended to have higher of Chebera, Sirri, Shita, Yora and Churchura villages. educational levels than the older respondents, and this Crops farmed included maize (Zea mays), teff (Eragrostis influenced the level of understanding of the importance of tef), banana (Musa acuminata), mango (Mangifera wildlife conservation among the educated people indica), avocado (Persea americana), ginger (Zingiber (Anthony, 2007; de Boer et al., 2013). Level of education officinale) and ‘Enset’ (Enset ventricosum). is a major factor in obtaining better employment opportunities and subsequently alternative livelihoods. Local people with higher educational levels participated in Focus group discussion agricultural activities as well as other activities like anti- poaching crusades, tour guiding and working in local The discussants have revealed that activities such as government organizations. Such activities tended to illegal hunting, livestock grazing, wildfire, fuel wood reduce their dependence on resources from the protected gathering, illegal farming practice, wild honey and green area. chilli collection were performed by the local people. Most The above are consistent with the assertion by Akama participants agreed that the local communities benefited et al. (1995) that the level of education varied inversely from the Park resources. Most of them described the with the level of negative attitudes towards the reserve shortage of private grazing land and decreased farmland and conservation activities. A low level of awareness holding due to the Park around them. This could have regarding conservation issues and protected area increased pressure on the Park area resources for management practices with the lack of involvement of the livestock grazing and agricultural expansion. They also local community in decision making processes might also emphasized additional farmland should be provided as be an important determinant of negative attitudes of the compensation and sharing of resource should be local people towards the present study area. As a factor, allowed. Some of the discussants noted that previously age has a significant influence on the attitudes of local they used to hunt different wild animals and minimize people towards conservation. Younger people have their threat. However, at present, the negative effects of tended to show positive attitudes toward conservation the animals are on the increase. As a result, some of the than the elderly, probably due to the fact that younger discussants were dissatisfied with the existence of respondents were more educated than adults. Older CCNP. They considered the Park as a limiting factor in respondents felt that the Park would threaten their improving their livelihood. Some of them also stated that livelihoods by reducing opportunities farm expansion as CCNP has been responsible for their restricted access to well as access to pasture land, fuel-wood and extraction resources in the area and further calmed forced of forest products. Similar results were reported for older relocation. Few discussants considered the Park as residents in around five protected areas in Tanzania useless. They also felt that Park staff members do not (Newmark et al., 1993). Occupations of the respondents like communities around the Park boundaries. But most also had some effect on their attitudes. Livestock holding discussants had positive attitude towards wildlife for its was an important predictor of the relationship between importance to attract tourists, hunting opportunities during local communities and the protected area. Those with drought, enjoyment derived from viewing wildlife and its higher numbers of livestock tend to have negative value for future generation. attitudes towards the protected area than those with fewer numbers of livestock. People with more cattle are more likely to interact with the protected area through DISCUSSION restrictive, prohibitive and punitive laws. They are likely to be arrested and fined if found with livestock in the Socio-demographic variables protected area.

Many factors such as different economic, legal, social and ecological concerns affect the attitude of local people Livestock grazing on conservation issues (Adams and Hulme, 2001). Among the socio-demographic factors examined in the Most of the local people around CCNP were dependent study area, education and age were important predictors on subsistence agriculture and livestock rearing for their of the relationship between local communities and the livelihoods. Livestock usually intensely compete with wild protected area. Education is one of important factor in animals for the same habitat resources, including forage understanding the role of protected areas in conservation, and water, and this might have strong impacts on wildlife and hence influences the attitudes of local people towards (Masanja, 2014). Cleaveland et al. (2002) indicated that Megaze et al. 53

interactions between livestock and wildlife populations revealed that illegal hunting was fueled by various are a key issue in livestock economies worldwide, factors, including the need for wild meat for household particularly in east and southern Africa, where many consumption and commercial trade in wild animal communities live in close contact with wildlife. Most of the products due to few alternative livelihood options and respondents considered the Park as their communal retaliate killings. The local people believed that hunting of pasture area and they did not agree that livestock should destructive wildlife is a good way to scare off crop raiding be banned from accessing the Park. It was observed that animals and reduce depredation of their livestock. The livestock encroached up to 5–10 km inside the Park to link between illegal hunting and human–wildlife conflict graze and access surface water during the dry seasons reported in this study is consistent with earlier reports and this might affect wildlife management practices. from elsewhere in Africa (Coad et al., 2010). For Extensive livestock encroachment in the predominantly example, in eastern and southern Africa, demand for wildlife grazing zone might lead to their direct or indirect more land for crop and livestock production has interactions with enhancing chances of disease increased antagonism between humans and wildlife, transmission (Rinderpest, Bovine TB and foot and mouth leading to illegal hunting (Wilfred, 2010). A large disease) and competition for forage resources, as well percentage of respondents admitted hunting crop-raiding influence wildlife habitat use. For example, the mineral animals and expressed great dissatisfaction with the Park spring water locally known as ‘hora’, which was used by authorities for not doing anything to prevent crop raiding wildlife, especially African buffaloes and elephants, is and predation of livestock. Focus group discussions also largely encroached by expanding livestock. As a result, indicated that farmers around CCNP regarded hunting as wild animals avoid use of ‘hora’ during the day time. The one of the effective methods to protect crops and negative impact of livestock activity on range quality of livestock from wildlife. Respondents who admitted wildlife might reduce the potential for ecotourism by hunting in the Park had farms located near the Park edge reducing the feasibility of wildlife viewing as indicated by and are therefore more likely to be affected economically Oladeji et al. (2012). The increase in livestock numbers in by crop raiding and depredation of livestock. Focus group the Park also resulted in increases in livestock depre- discussions also revealed that animal products dation by large carnivores and created conflict between commercially traded included ivory from African elephant local people with wildlife and the Park managements. (Loxodonta africana), skins from species such as leopard (Panthera pardus), lion (Panthera leo) and Colobus monkey. The mane of lions and leopard skin were used Firewood extraction to make helmets for male dancers during cultural ceremonies. Skin of large antelopes (e.g. bushbuck Firewood was the main source of energy for domestic (Tragelaphus sciptus) and African buffaloes (Syncerus purposes in the study area. Firewood extraction might caffer) were used to make traditional beds for adults and have a negative impact on wildlife because trees provide mats for drying grains, and for making traditional bags for a habitat for a wide range of wildlife (Bonjour et al., storage and carrying grains. Ivory was also used to make 2013). It might reduce feeding grounds and mating sites traditional dancing rings worn during the cultural of wildlife in the Park. Alternative fuel sources such as ceremonies. cattle dung, farm trees and agricultural residue were also Results of the present study suggest that illegal hunting used by the local people, and this might help reduce is strongly linked to distance of village from the Park pressure on firewood extraction from the Park. It was boundary. This relationship has also been reported in observed that in some villages, people travel long studies from other part of Africa (Coad et al., 2010), with distances (about 3 km) and spent more than two hours to higher levels of poaching by people living nearer the collect firewood. The problems of firewood extraction protected areas than those living father away. Most of the were more acute in the wet season of the year. They also study villages adjacent to CCNP were within 1 to 3 km of use thatch as roofing material, timber for house the reserve boundary, and these were the most construction and furniture and tree fodder as livestock problematic villages as far as poaching was concerned. feeds. This dependence on trees in the Park might Being closer to the reserve might be advantageous increase conflict between local people and Park officials because of easy or cost-effective access to wildlife and further affect wildlife management practices in the resources. Greater distances mean increased time, effort study area. and costs for hunters to find wildlife and transport meat or other wildlife products to homes or selling points. During the study period, it was observed that large numbers of Illegal hunting African elephants were found close to the Park headquarters, possibly for security reasons as reported Illegal hunting is a serious threat to the conservation by Balakrishnan and Ndhlovn (1992). Focus group status of many wildlife species in Africa (Coad, 2007). discussions indicated that wild honey collecting is one The CCNP, like many of Africa’s protected areas, is also cause of illegal hunting. Wild honey collection provided under increasing pressure from hunting. This study has legal reasons for entering the reserve, but managers and 54 Int. J. Biodivers. Conserv.

rangers complained that the majority of people use this its potential to cause fire outbreaks that might ravage the as a pretext for indulging in illegal activities, like hunting, Park and degrade the habitat quality of wildlife. According once inside the Park. Illegal hunters preferred a range of to the respondents, they set fires to protect themselves animal species with different body sizes. African and their livestock from predator attacks. Fires were also buffaloes (Syncerus caffer), African elephants (Loxodonta set along roads in the Park to clear footpaths for ease of africana), waterbuck (Kobus ellipsiprymnus), bushbuck walking and visibility. Human encroachment near (Tragelaphus scriptus), bush pig (Potamocherus protected areas contributed to increase in fire occurrences larvatus), common warthog (Phacochoerus africanus), in Gonarezhou National Park in Zimbabwe (Gandiwa et leopard (Panthera pardus) and lions (Panthera leo) were al., 2013). Field observations also indicated that during among the most targeted and preferred species. A variety the dry season the study area was left as a fire mosaic, of illegal hunting methods were used in the CCNP. with different areas burnt at different times. Regular Common hunting methods included snares, firearms, burning has significant ecological effects on the wildlife poisoning and hunting with dogs. Snares were the most living in the affected ecosystems. Some of the direct commonly reported hunting method in CCNP, probably effects of fire on fauna in ecosystems include direct and because they are, easy to use and versatile. indirect of smaller mammalian species and reptiles (Klop Respondents were suggested that with increased law and van Goethem, 2008). In CCNP, some animals like enforcement efforts in the area, illegal hunters were likely baboons, bush pigs (Potamocherus larvatus) and snakes to switch to less detectable methods such as snaring, have been recorded to have died as a result of wildfires. which is a particularly undesirable hunting technique from a conservation perspective. Snare were difficult to locate, making trapping challenging to control, as well as killing Illegal farming non-target species (Lindsey et al., 2012; Martin, et al., Illegal farming is another source of anthropogenic 2012). Firearms were most commonly used to hunt large pressure in CCNP. Focus group discussions revealed mammals such as African elephants, buffaloes and that historically, encroachment of wildlife habitats for common warthogs. In this study, crop and livestock agricultural activities and illegal hunting have occurred in losses might derive illegal hunting at a higher level. the Park. The local communities had encroached into the Poverty might also be a reason for hunting wild animals Park area for shifting cultivation over a long period of time in the area. As indicated by the respondents, wild meat is before the establishment of the Park. Human population the cheapest source of protein, representing an important growth around the Park and poverty might be the main source of meat for the poorest households around the reasons for clearing of land for agriculture as away of CCNP. Lindsey et al. (2011) reported in south-eastern increasing crop output because of limited alternative Zimbabwe that key drivers of the wild meat trade included survival strategies which increasingly causing destruction poverty and food shortages, failure to provide benefits to and outright loss of some important habitats in the Park communities, inadequate investment in anti-poaching in ecosystem. Field observations in CCNP indicate that the some areas under wildlife management and weak penalty growth rate of cultivated areas was high at the periphery systems that do not provide sufficient deterrent to illegal of protected areas. This might also be the cause of wild meat hunters. The results of this study are consistent human–wildlife conflict around the Park area. Chebera with studies in the Serengeti national park of Tanzania, Churchura National Park harbors many large mammal, which indicated that most local people considered wild birds and other wild animal species. Therefore, it can meat and wildlife body parts as sources of protein and serve as an important area for conservation of the means of generating income (Nielsen et al., 2013). Most country's wildlife and tourist attraction in the future. There of the respondents indicated that illegal hunting activities is a need to improve understanding of the ecological, in CCNP between the years 2012 to 2014 due to social and cultural dimensions of conflict situations in the strengthened law enforcement in the Park. area, to mitigate anthropogenic impacts in CCNP. The findings further suggest the need to initiate long-term monitoring to analyze trends in the incidences of human Wildfire impacts on wildlife resources. A combined strategy aimed

at improving local participation in wildlife conservation This study indicated that incidence of natural wildlife (e.g. initiatives, initiation of public education and awareness lightning) wildfires were lower than anthropogenically- campaigns and provision of alternative sources of income caused wildfires. Activities such as wild honey extraction, for the local people will reduce the threat, and contribute land clearing for shifting cultivation, obtaining good to improve conservation of wildlife in Chebera Churchura quality pasture for livestock, controlling harmful wildlife National Park. such as snakes and creation of fire-killed wood at the boundaries of the Park increased the occurrence of fire during the dry seasons. Honey collectors used many Conflict of Interests areas of the Park for traditional bee-hive hanging; a practice frowned upon by Park management because of The authors have not declared any conflict of interests. Megaze et al. 55

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